Sourcing Artificial Intelligence from Industry: What is Real [and What Isn’t]?

* Please note all CISAC events are scheduled using the Pacific Time Zone.

Seminar Recording: https://youtu.be/xUgzxG7MQa0

About the Event: The development and adoption of artificial intelligence (AI) technologies by the US military, and the ramifications of their adoption, has been the subject of many recent articles in both the popular as well as academic literature. Much of what has been said about them is speculative and even sensationalist, especially in regards to AI-enabled weapons. While at one time the US Department of Defense (DoD) was the driving force behind American science and technology research, and perhaps it still is in the case of certain niche technologies, there is no question that university and private sector research are advancing the state-of-the-art in AI, and the DoD is following behind. To that end, it is reasonable to assume that the majority of DoD AI technologies are sourced from industry using a combination of traditional acquisition vehicles, as defined in the Federal Acquisition Regulations, as well as non-traditional engagements, for example via the Defense Innovation Unit in Silicon Valley. In this talk I will summarize a number of recent public Requests for Information (RFIs) and Requests for Proposals (RFPs) to industry coming out of the DoD. I will use these RFIs and RFPs as a means to gauge the ‘state’ of AI in the DoD. My goal is to gain insight into what the DoD is actually trying to do with AI from amidst the public’s imagination and fear of what is possible, in order to better inform the public debate over AI ethics, governance, and other ramifications.

About the Speaker: Dr. David Blum is the Principal Data Scientist at Next Tier Concepts, where he supports the Office of the Secretary of Defense and the US Intelligence Community as a principal investigator, as well as a Lecturer at the Johns Hopkins University Applied Economics Program, where he teaches a course titled "Real Risk" covering the tools of probabilistic risk analysis and warning. He has more than 14 years of experience performing operations research and risk analysis for the US national security community. He previously served as Technical Director of the Operations Research and Systems Analysis Division for the Department of Defense's Joint Improvised-Threat Defeat Office (JIDO), where he oversaw the production of operations research analysis to support current military operations, and as an operations research scientist for several Defense Department and Intelligence Community offices. His assignments ranged from strategic assessments of future military force mixes, to tactical analyses to inform counter-terrorism operations, to development of automated processors for technical data exploitation at the national scale. He held a predoctoral fellowship at the Center for International Security and Cooperation, a Global Security graduate scholarship at Lawrence Livermore National Laboratory, and was a member of Stanford's Engineering Risk Research Group. He received his doctorate from Stanford University in management science and engineering, his Master's degree from Massachusetts Institute of Technology in political science, and his Bachelor's degree from Columbia University in history and physics, and has co-edited a book titled Counterterrorism and Threat Finance Analysis during Wartime. His research interests include crisis early warning and predictive analytics.